电子鼻在气体检测中的应用研究

优选对甲烷、丙烷及氢气交叉敏感的5只半导体传感器组成气体传感器阵列,建立实时数据采集系统,结合特征提取和模式识别算法,研制出了一种对3种可燃性气体进行实时检测的电子鼻系统。提出了双重神经网络定量分析多种未知气体的方法,即先利用第一重网络对气体进行定性识别,再应用第二重网络对识别出的气体进行定量分析。通过BP神经网络分析表明:该系统对3种气体的识别率达到了100%,定量分析的最大相对误差不超过9.4%。

Application research on electronic nose in multi-gas detection

Five semiconductor gas sensors sensitive to CH4,C3H8 and H2 are chosen to compose the gas sensor array,and an on-line data acquisition system is constructed.Combining with the algorithm of feature extraction and pattern recognition,an electronic nose system is developed for the real-time detection of the three combustible gases.The method of double neural network is proposed for quantitative analysis of multi-gas which is unknown.The first network is for gas qualitative analysis,and the second one is for gas quantitative analysis.Based on BP neural network analysis,the recognition rate of the three gases above is 100%,and the maximum relative error of quantitative analysis is not more than 9.4%.